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Formulation of Localized Damping Models for Large Displacement Analysis of Single-Degree-of-Freedom Inelastic Systems
Issues with traditional implementations of tangent-stiffness-proportional damping model are associated with negative damping forces that develop in the post-yield range when the system stiffness becomes negative and with unrealistic damping forces arising at degrees of freedom undergoing second-order movements only. To overcome these issues, this paper proposes a localized formulation of the tangent-stiffness-proportional damping model which can be used in nonlinear dynamic analysis of simple inelastic systems. Results show the consistency of the local and global damping formulations in small displacements and the effectiveness of the localized tangent-stiffness-proportional damping model in the presence of material and geometrical nonlinearities.
Formulation of Localized Damping Models for Large Displacement Analysis of Single-Degree-of-Freedom Inelastic Systems
Issues with traditional implementations of tangent-stiffness-proportional damping model are associated with negative damping forces that develop in the post-yield range when the system stiffness becomes negative and with unrealistic damping forces arising at degrees of freedom undergoing second-order movements only. To overcome these issues, this paper proposes a localized formulation of the tangent-stiffness-proportional damping model which can be used in nonlinear dynamic analysis of simple inelastic systems. Results show the consistency of the local and global damping formulations in small displacements and the effectiveness of the localized tangent-stiffness-proportional damping model in the presence of material and geometrical nonlinearities.
Formulation of Localized Damping Models for Large Displacement Analysis of Single-Degree-of-Freedom Inelastic Systems
De Francesco, G. (Autor:in) / Sullivan, T. J. (Autor:in)
Journal of Earthquake Engineering ; 26 ; 4235-4258
11.06.2022
24 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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